For the last decade on social media, Ruby Thelot has asked himself the same questions when he encounters viral content online: Is this an ad? Is this account real? Is this an actual trend or just a fluke?
While trends like “6-7” and “looksmaxxing” have recently broken containment, not every new term or subcultural phenomenon has real mainstream staying power. Remember, in years past, when tech bros tried to make NFTs a thing? Or that period when audio chat apps like Clubhouse were pitched as the future of social media but quickly flamed out? (A prediction WIRED was not immune to.)
Thelot, a cyber-ethnographer and media theory researcher at NYU, says overestimating trends happens because the internet has become “balkanized,” with each of us on our own “digital island,” where most seemingly viral phenomena are really just the result of force-fed consumption. This is where virality primarily exists today: between provinces, not among the masses.
Thelot’s book In Defense of Being-On-Line comes out this fall. WIRED recently spoke with him about why virality can be an outdated metric for understanding trends, the myth of dating burnout, and what the popularity behind prediction markets actually signals.
This interview has been edited for length and clarity.
JASON PARHAM: When determining if a trend is real, is the problem now that we mistake short-term engagement for long-term adoption?
RUBY THELOT: The problem with our attempt to understand culture is that what was once a good proxy, namely virality, has become a target in and of its own. Goodhart’s law [coined by British economist Charles Goodhart] tells us that when a measure becomes a target, it ceases to be a good measure. So people are architecting content and media in order to simply get to the goal of having a lot of views without thinking about the actual inherent value of the thing. And that inherent value is what actually gives it cultural staying power. Because we are so far into Goodhart’s law in terms of culture, you can engineer virality without it ever trickling down to culture.
Dating burnout has gotten a lot of attention over the last few years, which has pushed dating apps to rebrand around AI. In May, Bumble announced that it was killing its swipe feature to lure users back. But you say the narrative around burnout is a mirage.
Heteropessimism has been reported since 2019, and is about the general malaise that straight women have when dating straight men. What was interesting to me about this is that, of course, there is an existing group of people who feel this way.
A friend recently wrote a New York Times essay, “There’s Nothing Wrong With Wanting Men,” which was more of a hetero-optimist piece, and she needed to do that because there was a feeling of malaise. We took a look at posts on social media. I looked at Instagram and TikTok, around 1,000 videos that had over 1 million views. We wanted to know: What is the percentage of things that are actually negative?
What did the data tell you?
It hovered around 25 percent. And I wanted to compare—is there one platform that is more negative than the other? I’m trying to identify the different digital islands and see if there is an area where this specific comment is getting sent where it’s specifically more negative, like X has a trickier algorithm where things are a bit more negative. So I do think heteropessimism is a little overblown by culture writers, and I say that as someone who writes for magazines.
One beloved industry right now is prediction markets. On Kalshi and Polymarket, droves of young people are betting on everything from Bad Bunny’s Super Bowl halftime performance to the wildfires in Oregon. What does its widespread adoption signal?
I spent some time studying groups of young men who were trading meme coins in 2020 to 2024. This was a similar kind of activity; it is mostly gambling. What I discovered was that oftentimes the activity of gambling was not an individual activity. It tended to be in these group chats, lovingly called “the trenches,” in which you and your boys exchanged information and traded together. And not only that, you lose together.
When I think about the male loneliness epidemic, this was a rather twisted but interesting novel form of male bonding. With prediction markets, I think about them not merely as financial instruments, but also as a tool for participation. Consumers no longer want to just purely consume, they want to participate in culture.
So they buy into culture as a way of participating?
But I don’t even think that the financial award is what is driving people to gamble. If you’re spending eight hours on the screen, the question is not “How do I make money with this?” It is “How do I get closer to it?” The bet, for the most part, does not matter. Because we live in a highly financialized world, what matters is the closeness to the media, and you get close through the act of wagering or betting.
AI is reshaping culture at light speed. Which prediction about it do you think people will laugh at in 10 years?
I don’t think AI is going to end the world. And the reason is that I don’t think intelligence is that important.
In what sense?
Most of our issues in the world are not bottlenecked by intelligence, but by the promise of cooperation, coordination, and essentially alignment of large groups of people toward a common shared goal. That’s the first part. The second thing is, when you start to quantify specific things, once again, the metric becomes the goal in and of itself.
The belief that intelligence is the most powerful thing comes from the assumption that there’s a group of people on this planet who are the most intelligent. Sir Francis Galton, the father of eugenics, also believed this. With AI, they are just projecting what they value about themselves onto the superintelligence. It’s philosophically unsound and actually quite dangerous.
Why dangerous?
In that process, you’re foreclosing a whole slew of untapped values—emotional intelligence, bodily intelligence, artistic intelligence. This is a concept the French philosopher Gilbert Simondon talks about. With each new advancement, certain things are left behind. And I think we might be leaving behind a whole set of highly human, alternative intelligences that are not measured or quantified by our current systems.
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